The need for scientific rigour and accountability in flood mapping to better support disaster response

Schumann, Guy

doi:10.1002/hyp.13547

Cited by 14 publications

(4 citation statements)

References 30 publications

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“…There is an interest in accounting for and communicating uncertainties of flood inundation maps [192]. However, the computational cost associated with the forecast runs of multiple model realizations results in unfeasible real-time operational applicability of the traditional ensemble approach.…”

Section: Flood Inundation Simulationmentioning

confidence: 99%

Recent Advances in Real-Time Pluvial Flash Flood Forecasting

Zanchetta

Coulibaly

2020

Water

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Recent years have witnessed considerable developments in multiple fields with the potential to enhance our capability of forecasting pluvial flash floods, one of the most costly environmental hazards in terms of both property damage and loss of life. This work provides a summary and description of recent advances related to insights on atmospheric conditions that precede extreme rainfall events, to the development of monitoring systems of relevant hydrometeorological parameters, and to the operational adoption of weather and hydrological models towards the prediction of flash floods. With the exponential increase of available data and computational power, most of the efforts are being directed towards the improvement of multi-source data blending and assimilation techniques, as well as assembling approaches for uncertainty estimation. For urban environments, in which the need for high-resolution simulations demands computationally expensive systems, query-based approaches have been explored for the timely retrieval of pre-simulated flood inundation forecasts. Within the concept of the Internet of Things, the extensive deployment of low-cost sensors opens opportunities from the perspective of denser monitoring capabilities. However, different environmental conditions and uneven distribution of data and resources usually leads to the adoption of site-specific solutions for flash flood forecasting in the context of early warning systems.

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Section: Flood Inundation Simulationmentioning

confidence: 99%

Recent Advances in Real-Time Pluvial Flash Flood Forecasting

Zanchetta

Coulibaly

2020

Water

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“…The interest of the industry and governments is a driver for the development of new algorithms and techniques that, inevitably, contribute to the increase of the knowledge in the field. However, as argued by Schumann [214], there are issues related to the accountability of the products, since validation and uncertainty assessments are not always conducted thoroughly. Indeed, as discussed in [215], while there are several good reasons to overlook uncertainty analysis, the provisioning of information about the accuracy of the products is fundamental, as they could be used by decision makers in emergency response [216].…”

Section: Discussionmentioning

confidence: 99%

Flood Detection with SAR: A Review of Techniques and Datasets

Amitrano,

Di Martino,

Di Simone

et al. 2024

Remote Sensing

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Floods are among the most severe and impacting natural disasters. Their occurrence rate and intensity have been significantly increasing worldwide in the last years due to climate change and urbanization, bringing unprecedented effects on human lives and activities. Hence, providing a prompt response to flooding events is of crucial relevance for humanitarian, social and economic reasons. Satellite remote sensing using synthetic aperture radar (SAR) offers a great deal of support in facing flood events and mitigating their effects on a global scale. As opposed to multi-spectral sensors, SAR offers important advantages, as it enables Earth’s surface imaging regardless of weather and sunlight illumination conditions. In the last decade, the increasing availability of SAR data, even at no cost, thanks to the efforts of international and national space agencies, has been deeply stimulating research activities in every Earth observation field, including flood mapping and monitoring, where advanced processing paradigms, e.g., fuzzy logic, machine learning, data fusion, have been applied, demonstrating their superiority with respect to traditional classification strategies. However, a fair assessment of the performance and reliability of flood mapping techniques is of key importance for an efficient disasters response and, hence, should be addressed carefully and on a quantitative basis trough synthetic quality metrics and high-quality reference data. To this end, the recent development of open SAR datasets specifically covering flood events with related ground-truth reference data can support thorough and objective validation as well as reproducibility of results. Notwithstanding, SAR-based flood monitoring still suffers from severe limitations, especially in vegetated and urban areas, where complex scattering mechanisms can impair an accurate extraction of water regions. All such aspects, including classification methodologies, SAR datasets, validation strategies, challenges and future perspectives for SAR-based flood mapping are described and discussed.

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“…Timely predictions of flood extent and depth from flood forecasting systems provide essential information to flood risk managers that enable anticipatory action prior to the occurrence of a potential flooding event. Evaluating the accuracy of flood extent forecasts against observations forms an essential part of model development (Schumann, 2019). Forecast flood inundation footprints are typically validated against remote sensing images using binary performance measures (Stephens et al, 2014(Stephens et al, ) calculated at grid level.…”

Section: Introductionmentioning

confidence: 99%

“…It is not meaningful to compare verification scores across different spatial scales. Spatial verification methods for flood inundation mapping have only received limited attention over the past decade (Schumann, 2019).…”

Section: Introductionmentioning

confidence: 99%